Artificial Intelligence Course Outline

Course Material Text books: Artificial Intelligence: Structures and Strategies for Complex Problem Solving (4th ed.), George F. Luger, Addison-Wesley http://www.cs.unm.edu/~luger/ai-final/ Artificial Intelligence, A Modern Approach, Stuart Russell and Peter Norvig, Prentice Hall http://aima.cs.berkeley.edu/

Course Description Artificial Intelligence is the subfield of computer science concerned with automating tasks that would require "intelligence" if performed by people. AI is a highly eclectic field, with roots in mathematics, logic, psychology, philosophy, and engineering. The goal of this course is to introduce and survey the field of Artificial Intelligence, paying special attention to foundational concepts and theories. In addition, current trends and approaches in AI research will be studied

Course Outline Course overview and Introduction to AI AI history LOGIC PROGRAMMING Predicate logic, Prolog Prolog Basics Prolog: unification, Resolution, lists More Prolog: built-in predicates, Operators AI AS SEARCH State spaces, uninformed strategies Constraint-based search

Course Outline (contd.) Heuristics, Informed strategies Optimization problems, Game Trees REPRESENTATION & AI Semantic nets, Frames Expert Systems, Uncertainty Rule-based Reasoning MACHINE LEARNING Connectionist Models Emergent Models Genetic Algorithms, a-life Case Studies: Eliza, Mycin Student presentations

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